def __init__(self):
Ftrace.__init__(self)
self.function_available_file = self.tracing_dir + "available_filter_functions"
self.function_filter_file = self.tracing_dir + "set_ftrace_filter"
self.tracer_name = "function"
self.CONFIG_DYNAMIC_FTRACE = "CONFIG_DYNAMIC_FTRACE"
def __init__(self, kprobe_filter=None):
Ftrace.__init__(self)
self.events_dir = self.tracing_dir + "/events/kprobes/"
self.events_file = self.tracing_dir + "/kprobe_events"
self.trace_enable_file = self.events_dir + "/enable"
self.kprobe_filter = kprobe_filter
self.required_config_options = ["CONFIG_KPROBE_EVENTS"]
self.pre_flight_checks()
def parse_file(filepath):
trace = Ftrace(filepath)
return (filepath, trace)
parser.add_argument('-f',
'--file',
dest='file',
help='File (systrace/ftrace log) to parse')
args = parser.parse_args()
# Multi-core usage
sb_all = DataFrame(columns=ALL_CPUS)
arrays = [['BIG'] * 5 + ['LITTLE'] * 5, range(5) + range(5)]
multi_index = MultiIndex.from_tuples(list(zip(*arrays)),
names=['cluster', 'num_cores'])
sb_by_cluster = DataFrame(index=multi_index)
trace = Ftrace(args.file)
total_duration = trace.duration
# Freq
df_freq = DataFrame(index=ALL_CPUS)
df_freq.fillna(0, inplace=True)
# LPM
LPM_states = {
-1: 'Busy',
0: 'WFI',
1: 'Retention',
2: 'SPC (GDHS)',
3: 'PC'
}
df_lpm = DataFrame(index=ALL_CPUS, columns=LPM_states.values())
import ftrace
from ftrace import Ftrace
from pandas import DataFrame
LITTLE_CLUSTER_MASK = 0x0F
BIG_CLUSTER_MASK = 0xF0
FREQ_ALL_CORES = [
0, 480000, 807000, 1018000, 1210000, 1306000, 1517000, 1805000, 2016000,
2304000, 2515000
]
LITTLE_CPUS = ftrace.common.unpack_bitmap(LITTLE_CLUSTER_MASK)
BIG_CPUS = ftrace.common.unpack_bitmap(BIG_CLUSTER_MASK)
ALL_CPUS = LITTLE_CPUS.union(BIG_CPUS)
# processing scripts for each file in directory
trace = Ftrace(r'Z:\EAS\Mate8_Default\music1.html')
df_freq = DataFrame(index=ALL_CPUS, columns=FREQ_ALL_CORES)
df_freq.fillna(0, inplace=True)
for cpu in range(8):
for busy_interval in trace.cpu.busy_intervals(cpu=cpu):
print "busy: " + str(busy_interval)
for freq in trace.cpu.frequency_intervals(
cpu=cpu, interval=busy_interval.interval):
print "freq: " + str(freq)
df_freq.loc[cpu, freq.frequency] += freq.interval.duration
from pandas import DataFrame
from collections import defaultdict
import ftrace
from ftrace import Ftrace
from ftrace import Interval
#trace.gpu.busy_time(interval=it)/it.duration
#trace.gpu.idle_time(interval=it)/it.duration
#trace.gpu.lpm_time(interval=it, state=ftrace.gpu.BusyState.NAP)/it.duration
#trace.gpu.lpm_time(interval=it, state=ftrace.gpu.BusyState.SLUMBER)/it.duration
# processing scripts for each file in directory
trace = Ftrace(r'C:\Users\c00759961\Documents\systrace\Baidu_scroll.html')
#print trace.android.framerate()
#print trace.gpu.frequency_intervals(interval=it) # trace.clock.frequency_intervals(clock='oxili_gfx3d_clk', interval=it)
#trace.bus.bimc_aggregate_requests(interval=it)
#print trace.cpu.seen_tasks(cpu=0)
#print trace.android.event_intervals(name='VSYNC')
#ti = ftrace.Interval(0, 0.0005)
#print trace.thermal.
#print trace.cpu.task_intervals(cpu=4, interval=ti)
#print trace.cpu.runqueue_depth_intervals(cpu=4, interval=ti)
#print trace.cpu.task_intervals(task=tt)[0]
#print "Input Latency\n----------------\n"
#print trace.android.rendering_intervals() #'irq/13-fts_touc'
#print "Switch Camera Latency\n----------------\n"
#print trace.camera.switch_device_intervals()
#print trace.android.event_intervals('AndroidCamera.open')
#print "\n----------------\n"
#print "FPS: {}".format(trace.android.framerate())
##print trace.cpu.idle_intervals(cpu=0)
#total_duration = trace.duration if not INTERVAL else INTERVAL.duration
return Series(data=data.values(), index=data.keys(), name=trace.filename) / total_duration
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Power/Performance analysis of HMP platforms!')
parser.add_argument('-t', '--time', dest='time',
help='hope to capture how long logs')
args = parser.parse_args()
#get all logs for analysis
os.system('python getPhoneLogs.py -t ' + args.time)
if os.path.exists(get_out_systrace_path()):
trace = Ftrace(get_out_systrace_path())
else:
print 'error'
exit(1)
total_duration = trace.duration
print 'trace.duration is ' + str(trace.duration)
#get config from phone
CLUSTER_CFG = get_cluster_config()
CLUSTER_RELATED_CPUS = get_cluster_related_cpus()
CLUSTER_AVAILABLE_FREQS = get_available_freqs()
ALL_CPUS = get_all_cpus()
# Multi-core usage
sb_all = DataFrame(columns=ALL_CPUS)
def __init__(self):
Ftrace.__init__(self)
self.events_dir = self.tracing_dir + "/events/block"
self.filter_file = self.tracing_dir + "/events/block/filter"
self.trace_enable_file = self.events_dir + "/enable"
def parse_file(filepath):
trace = Ftrace(filepath, ['tsens_threshold_hit', 'tsens_read', 'tsens_threshold_clear', 'clock_set_rate'])
return (filepath, trace)
"tsens_tz_sensor2": "pop_mem",
"tsens_tz_sensor6": "cpu7",
"tsens_tz_sensor7": "cpu0",
"tsens_tz_sensor8": "cpu1",
"tsens_tz_sensor9": "cpu2",
"tsens_tz_sensor10": "cpu3",
"tsens_tz_sensor12": "gpu",
"tsens_tz_sensor13": "cpu4",
"tsens_tz_sensor14": "cpu5",
"tsens_tz_sensor15": "cpu6",
}
CLKS =['a57_clk', 'a53_clk', 'oxili_gfx3d_clk']
trace = Ftrace(r'C:\Users\c00759961\Documents\temp\nina-MDA35B-camera-UHD-recording-after.html',
['tsens_read', 'tsens_threshold_clear', 'tsens_threshold_hit',
'clock_set_rate', 'clock_enable', 'clock_disable'])
start = Timestamp('1/1/1970')
#end = start + Second(trace.duration)
NAMES = [TSENS_ALIAS[tsens] for tsens in trace.thermal.names if tsens in TSENS_ALIAS] + CLKS
df_therm = DataFrame(columns=NAMES)
#index=period_range(start=start, end=end, freq='1U')
for tsens in trace.thermal.names:
for therm in trace.thermal.temp_intervals(tsens=tsens):
df_therm.loc[start + Micro(therm.interval.end*1e6), TSENS_ALIAS[tsens]] = therm.temp
# lets look at clocks.
for clk in CLKS:
for freq_event in trace.clock.frequency_intervals(clock=clk):
"tsens_tz_sensor9": "cpu2",
"tsens_tz_sensor10": "cpu3",
"tsens_tz_sensor12": "gpu",
"tsens_tz_sensor13": "cpu4",
"tsens_tz_sensor14": "cpu5",
"tsens_tz_sensor15": "cpu6",
}
CLKS = ['a57_clk', 'a53_clk', 'oxili_gfx3d_clk']
start = Timestamp('1/1/1970')
if __name__ == '__main__':
trace = Ftrace(filepath, [
'tsens_threshold_hit', 'tsens_read', 'tsens_threshold_clear',
'clock_set_rate'
])
# duration
total_duration = trace.duration
# Thermal
NAMES = [
TSENS_ALIAS[tsens]
for tsens in trace.thermal.names if tsens in TSENS_ALIAS
] + CLKS
df_therm = DataFrame(columns=NAMES)
for tsens in trace.thermal.names:
for therm in trace.thermal.temp_intervals(tsens=tsens, interval=None):
df_therm.loc[start + Micro(therm.interval.start * 1e6),
TSENS_ALIAS[tsens]] = therm.temp
def parse_file(filepath):
trace = Ftrace(filepath, tracepoints='sched_hmp_migrate')
return (filepath, trace)
